Gravis Robotics, a Swiss ConTech company, just raised $200 million from SoftBank to make existing excavators and heavy machinery autonomous, hitting a $1 billion valuation and becoming Europe's newest robotics unicorn.
Switzerland's Gravis Robotics just pulled off something remarkable. The company, which builds autonomous technology for heavy machinery, raised a massive Series A round that pushed its valuation past the $1 billion mark. That officially makes it Europe's newest unicorn in the robotics space.
The round came in at $200 million, with SoftBank as the sole investor. According to Gravis, this is the largest Series A financing in construction robotics history. It follows a $22 million round in 2025, which we covered back then.
### What Gravis Actually Does
Here's the thing that makes Gravis different: they don't build robots from scratch. Instead, they retrofit existing excavators and other heavy equipment with their technology. It's called the Gravis Rack, and it combines sensors, computing hardware, and software to make machines autonomous.
The company was founded in 2022 as a spinout from ETH Zurich. The leadership team includes co-founder and CEO Ryan Luke Johns, co-founder and CTO Dominic Jud, and ETH Zurich robotics professor Marco Hutter as co-founder and board member.
Their approach is pragmatic. Construction companies don't want to replace their entire fleets. They want to make what they already own work smarter. Gravis has adapted its tech for more than a dozen brands and models, from roughly 22,000-pound machines up to substantially larger ones.
### The Vision: Operators in Control, Not Out of Work
Ryan Luke Johns, co-founder and CEO, puts it plainly: "It's not about taking operators out of the machine. It's about getting machines to be 30 percent more productive, to get an operator to drive multiple highly productive machines."
So we're not talking about eliminating jobs here. We're talking about making one operator capable of running several machines at once. The autonomous systems handle driving, trench digging, bulk excavation, truck loading, and stockpile management. When a job gets complicated, the operator can take manual control. When it gets repetitive, they hand it back to the system.
Johns describes it simply: "You press play, the machine will drive itself to the start and essentially do that entire job without intervention."
### A Broader Surge in Construction Robotics
This isn't happening in a vacuum. The Series A comes amid continued investment into European construction robotics, physical AI, and autonomous machinery through 2026.
- Amsterdam-based Monumental raised $31 million to scale its construction robotics fleet
- Espoo-based Hyperion Robotics secured $7.4 million for robotic microfactories
- Nature Robots, Trener Robotics, Nomagic, KEMARO, and Exclaim Robotics also raised rounds
Together, these adjacent rounds bring 2026 financings to roughly $93 million. Including Gravis, the selected funding total reaches about $293 million. Notably, KEMARO and Exclaim Robotics are also Swiss, pointing to an active robotics scene in Switzerland.
### Why Investors Are Paying Attention
Archie Muirhead, Partner at IQ Capital, which invested in the 2025 round, explains the appeal. "Ryan and the Gravis team identified a fundamental constraint facing construction at a time when demand for new infrastructure from compute to energy is accelerating โ a shortage of skilled operators."
He points to years of reinforcement learning and control policy research at ETH Zurich. "Gravis's technology is already delivering measurable productivity gains on live projects across four continents." He adds that this funding "cements Gravis' position as the leading construction autonomy company building into an enormous global total addressable market."
The company says its systems are now in use across four continents, with customers and partners including major players in the construction industry. As demand for new infrastructure continues to climb, the shortage of skilled operators isn't going away. Gravis is betting that making existing machines smarter is the fastest way to close that gap.